1H-NMR-based metabolic profiling identifies non-invasive diagnostic and predictive urinary fingerprints in 5q spinal muscular atrophy

Orphanet Journal of Rare Diseases

Musa Kockaya¹  Hartmut Schäfer²  Claire Cannet²  Manfred Spraul²  Andreas Hahn³  Wolfgang Wick⁴  Markus Weiler⁴  Andreas Roos⁵  Ulrike Schara⁵  Jessika Johannsen⁶  Stefan Kölker⁷  Jürgen G. Okun⁷  Friedrich K. Trefz⁷  Georg F. Hoffmann⁷  Afshin Saffari⁷  Andreas Ziegler⁷  Wolfgang Müller-Felber⁸  Astrid Blaschek⁸  Katharina Vill⁸  Romy Kirsten⁹ 

[1] ;Bruker BioSpin GmbH;Department of Child Neurology, University Hospital Gießen;Department of Neurology, Heidelberg University Hospital;Department of Neuropediatrics, Developmental Neurology and Social Pediatrics, Centre for Neuromuscular Disorders in Children, Children’s University Clinic Essen, University of Duisburg-Essen;Department of Pediatrics, Neuropediatrics, University Medical Center Hamburg-Eppendorf;Division of Child Neurology and Metabolic Medicine, Center for Child and Adolescent Medicine, Heidelberg University Hospital;Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, LMU Hospital, Dr. von Hauner Children’s Hospital;NCT Liquidbank, National Center for Tumor Diseases;

关键词: Spinal muscular atrophy;    SMA;    Metabolic profiling;    1H-nuclear magnetic resonance;    NMR;    Urinary fingerprints;   

DOI  :  10.1186/s13023-021-02075-x

来源: DOAJ

【 摘 要 】

Abstract Background 5q spinal muscular atrophy (SMA) is a disabling and life-limiting neuromuscular disease. In recent years, novel therapies have shown to improve clinical outcomes. Yet, the absence of reliable biomarkers renders clinical assessment and prognosis of possibly already affected newborns with a positive newborn screening result for SMA imprecise and difficult. Therapeutic decisions and stratification of individualized therapies remain challenging, especially in symptomatic children. The aim of this proof-of-concept and feasibility study was to explore the value of 1H-nuclear magnetic resonance (NMR)-based metabolic profiling in identifying non-invasive diagnostic and prognostic urinary fingerprints in children and adolescents with SMA. Results Urine samples were collected from 29 treatment-naïve SMA patients (5 pre-symptomatic, 9 SMA 1, 8 SMA 2, 7 SMA 3), 18 patients with Duchenne muscular dystrophy (DMD) and 444 healthy controls. Using machine-learning algorithms, we propose a set of prediction models built on urinary fingerprints that showed potential diagnostic value in discriminating SMA patients from controls and DMD, as well as predictive properties in separating between SMA types, allowing predictions about phenotypic severity. Interestingly, preliminary results of the prediction models suggest additional value in determining biochemical onset of disease in pre-symptomatic infants with SMA identified by genetic newborn screening and furthermore as potential therapeutic monitoring tool. Conclusions This study provides preliminary evidence for the use of 1H-NMR-based urinary metabolic profiling as diagnostic and prognostic biomarker in spinal muscular atrophy.

【 授权许可】

Unknown